Associate SDET Specialist

Role Overview: You will be responsible for designing, developing, implementing, testing, and maintaining automated test suites and frameworks for AI/ML pipelines. Collaboration with ML engineers and data scientists to understand model architectures and data workflows will be a key aspect of your role. Additionally, you will develop and execute test plans, test cases, and test scripts to identify software defects in AI/ML applications, ensuring the end-to-end quality of solutions including data integrity, model performance, and system integration. Implementing continuous integration and continuous deployment (CI/CD) processes for ML pipelines, conducting performance and scalability testing for AI/ML systems, documenting and tracking software defects, participating in code reviews, and fostering a culture of quality and continuous improvement within the ML engineering group are also part of your responsibilities. Staying updated with the latest trends and best practices in AI/ML testing and quality assurance is essential. Key Responsibilities: - Design, develop, implement, test, and maintain automated test suites and frameworks for AI/ML pipelines. - Collaborate closely with ML engineers and data scientists to understand model architectures and data workflows. - Develop and execute test plans, test cases, and test scripts to identify software defects in AI/ML applications. - Ensure end-to-end quality of AI/ML solutions, including data integrity, model performance, and system integration. - Implement continuous integration and continuous deployment (CI/CD) processes for ML pipelines. - Conduct performance and scalability testing for AI/ML systems. - Document and track software defects using bug-tracking systems, and report issues to development teams. - Participate in code reviews and provide feedback on testability and quality. - Help foster a culture of quality and continuous improvement within the ML engineering group. - Stay updated with the latest trends and best practices in AI/ML testing and quality assurance. Qualification Required: - Bachelors degree in Computer Science, Engineering, or a related field. - 2+ years of experience in quality assurance, specifically testing AI/ML applications. - Strong programming skills in Python (experience with libraries like PyTest or unittest). - Familiarity with machine learning frameworks (TensorFlow, PyTorch, or scikit-learn). - Experience with test automation tools and frameworks. - Knowledge of CI/CD tools (Jenkins, GitLab CI, or similar). - Experience with containerization technologies like Docker and orchestration systems like Kubernetes. - Proficient in Linux operating systems. - Familiarity with version control systems like Git. - Strong understanding of software testing methodologies and best practices. - Excellent analytical and problem-solving skills. - Excellent communication and collaboration skills.,